Simulation Comparing Factor Analysis, Mice, Average, and Truth

# ###FOR Sensitivity Analysis
# for (i in seq(1,24,4)){
#   print(ggarrange(plot_list[[i]],
#             plot_list[[i+1]],
#             plot_list[[i+2]], ncol=3, common.legend = TRUE, legend="bottom",align = c("h")))
# }

###FOR from truth

# cor.plot(data_frame_list[[2]][[3]][,,3],
#          main = "ATBC True Correlation")
# 
# cor.plot(data_frame_list[[52]][[3]][,,3],
#          main = "PLCO True Correlation")
# 
# 
# for (i in seq(1,44,4)){
#   print(annotate_figure(ggarrange(plot_list[[i]],
#                                   plot_list[[i+2]],
#                                   ncol=2, common.legend = TRUE, legend="bottom",align = c("hv")),top = "ATBC"))
#   print(annotate_figure(ggarrange(plot_list[[i+50]],
#                                   plot_list[[i+2+50]],
#                                   ncol=2, common.legend = TRUE, legend="bottom",align = c("hv")),top = "PLCO"))
#   
#   # if (i == 9){
#   #   cor.plot(data_frame_list[[i+1]][[2]][,,1], main = "Mice Median Correlsation for Factor = 0")
#   #   cor.plot(data_frame_list[[i+1]][[1]][,,1], main = "Factor Analysis Correlation for Factor = 0")
#   #   cor.plot(data_frame_list[[i+1]][[3]][,,1], main = "True Correlation for Factor = 0")
#   # }
# }